Open Access   Article Go Back

Performance Evaluation of ACO and PSO Task Scheduling Algorithms in Cloud Environment

D. Gupta1 , H.J.S. Sidhu2

  1. CSE, Desh Bhagat University, Mandi Gobindgarh, India.
  2. CSE, Desh Bhagat University, Mandi Gobindgarh, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-3 , Page no. 161-164, Mar-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i3.161164

Online published on Mar 30, 2018

Copyright © D. Gupta, H.J.S. Sidhu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: D. Gupta, H.J.S. Sidhu, “Performance Evaluation of ACO and PSO Task Scheduling Algorithms in Cloud Environment,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.161-164, 2018.

MLA Style Citation: D. Gupta, H.J.S. Sidhu "Performance Evaluation of ACO and PSO Task Scheduling Algorithms in Cloud Environment." International Journal of Computer Sciences and Engineering 6.3 (2018): 161-164.

APA Style Citation: D. Gupta, H.J.S. Sidhu, (2018). Performance Evaluation of ACO and PSO Task Scheduling Algorithms in Cloud Environment. International Journal of Computer Sciences and Engineering, 6(3), 161-164.

BibTex Style Citation:
@article{Gupta_2018,
author = {D. Gupta, H.J.S. Sidhu},
title = {Performance Evaluation of ACO and PSO Task Scheduling Algorithms in Cloud Environment},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2018},
volume = {6},
Issue = {3},
month = {3},
year = {2018},
issn = {2347-2693},
pages = {161-164},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1777},
doi = {https://doi.org/10.26438/ijcse/v6i3.161164}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i3.161164}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1777
TI - Performance Evaluation of ACO and PSO Task Scheduling Algorithms in Cloud Environment
T2 - International Journal of Computer Sciences and Engineering
AU - D. Gupta, H.J.S. Sidhu
PY - 2018
DA - 2018/03/30
PB - IJCSE, Indore, INDIA
SP - 161-164
IS - 3
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
547 389 downloads 270 downloads
  
  
           

Abstract

Use of cloud technology for different requirements of an organization is on increase. Number of companies like Amazon, Microsoft, Salesforce, etc. is leading the package of cloud services. The main objective of these companies is to ensure that right resources are assigned to clients so that the resources are not left underutilized. Cloud task scheduling is a key research area and every company is investing a lot into it to reduce the underutilization of resources and ensuring the tasks finish on time. Metaheuristic algorithms over time have been used extensively for this task. This paper analyzes the performance of two metaheuristic algorithms namely ACO & PSO for cloud task scheduling.

Key-Words / Index Term

ACO, PSO, VM, SJF, IAAS, PAAS, SAAS, Data Centre, Cloud Computing, ETC

References

[1] Celesti, A., Fazio, M., Villari, M., Puliafito, A., “Virtual machine provisioning through satellite communications in federated cloud environments.” Futur Gener Comput Syst 28(1), 85–93 (2012)
[2] Buyya, R., Broberg, J., Goscinski, A. (eds.): “Cloud Computing, Principles and Paradigms”. Wiley, Hoboken (2011)
[3] M. Kalra, S. Singh, “A review of metaheuristic scheduling technique in cloud computing”, Cairo University, Egyptian Informatics Journal, Vol. 16, issue 3, pp 275-295, 2015.
[4] Anitha H M, P. Jayarekha , "Security Challenges of Virtualization in Cloud Environment", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.1, pp.37-43, 2018..
[5] M. Tawfeek, A. El-Sisi, A. Keshk, F. Torkey, “ Cloud Task Scheduling Based on Ant Colony Optimization” ,The International Arab Journal of Information Technology, Vol. 12, No. 2, March 2015.
[6] N. Siddique, H. Adeli, “Nature Inspired Computing: An Overview and Some Future Directions”, Cong Comput, Vol 7, 706-714, 2015.
[7] A. Xu, Y. Yang, Z. Mi, “Task Scheduling algorithm based on PSO in cloud environment”, IEEE 12th International Conference on Autonomic and Trusted Computing, 978-1-4673-7212-1, 2015.
[8] F. Ramezani, J. Lu, F. K. Hussain. “Task-Based System Load Balancing in Cloud Computing Using Particle Swarm Optimization”, International Journal on Parallel Programming, Volume 42, Issue 5, pp 739–754, 2014.
[9] Shruti, M. Sharma, “Task Scheduling and Resource Optimization in Cloud Computing using Deadline-Aware Particle Swarm Technique”, International Journal of Computer Science and Engineering”, Vol. 5, Issue 6, pp. 227-231, 2017.